An Extremal Optimization approach to parallel resonance constrained capacitor placement problem
This work addresses the problem of reducing technical losses and preventing resonance issues in electrical distribution networks for utility operators, representing an incremental improvement over prior methods.
The authors tackled the optimal capacitor placement problem in distribution networks by incorporating resonance constraints to prevent capacitors from becoming harmonic sources, achieving significant gains compared to existing post-optimization repair methods.
Installation of capacitors in distribution networks is one of the most used procedure to compensate reactive power generated by loads and, consequently, to reduce technical losses. So, the problem consists in identifying the optimal placement and sizing of capacitors. This problem is known in the literature as optimal capacitor placement problem. Neverthless, depending on the location and size of the capacitor, it may become a harmonic source, allowing capacitor to enter into resonance with the distribution network, causing several undesired side effects. In this work we propose a parsimonious method to deal with the capacitor placement problem that incorporates resonance constraints, ensuring that every allocated capacitor will not act as a harmonic source. This proposed algorithm is based upon a physical inspired metaheuristic known as Extremal Optimization. The results achieved showed that this proposal has reached significant gains when compared with other proposals that attempt repair, in a post-optimization stage, already obtained solutions which violate resonance constraints.